NEIGHBOURHOOD DISADVANTAGES AND ATTITUDE TO SCHOOLING IN POOR URBAN SETTLEMENT IN NIGERIA: IMPLICATIONS FOR DEVELOPMENT

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1 NEIGHBOURHOOD DISADVANTAGES AND ATTITUDE TO SCHOOLING IN POOR URBAN SETTLEMENT IN NIGERIA: IMPLICATIONS FOR DEVELOPMENT Adenike E. Idowu 1, Emmanuel O. Amoo 2, Mofoluwake P. Ajayi 1, Bose J. Odewale 2, Ajibade E. Jegede 1, Olujide Adekeye 3 1 Sociology Department, Covenant University, Ota, Ogun State (NIGERIA) 2 Demography and Social Statistics, Covenant University, Ota, Ogun State (NIGERIA) 3 Psychology Department, Covenant University, Ota, Ogun State (NIGERIA) Abstract The challenges facing students in 21 st century are enormous especially the adolescents in secondary schools in distress and adverse neighbourhood environment. However, only limited studies have explained the interrelationships between neighbourhood environment (such as poverty, violence and its associate stress and crime) and reading culture, academic learning and performance, school dropouts, unemployable school leavers and the existence of widening gap in economic opportunities. The paper examined association between urban neighbourhood disadvantages with poor cognitive and behavioural disposition on schooling, learning and performance. Data for the study were extracted from a cross sectional survey among 1220 senior secondary schools students selected in equal proportion from 14 secondary schools in Lagos metropolis with attrition rate of 12.9%. The state was selected for being a representative of tribe and culture, urban rich and poor setting. The study adopted a measuring scale for both adverse environment and students disposition. The data were analyzed using univariate and binary logistic regression analysis. The findings suggest, among others, that adverse neighbourhood characteristics in urban center are connected with the poor learning attitude and learning outcomes. It recommends simultaneous emphasis on attitudinal change motivations and compulsory secondary education policy initiatives in Nigeria and across other sub- Saharan African countries. Keywords: Learning, neighborhood, adolescent, academic performance. 1 INTRODUCTION Schooling more specifically refer to formal instruction in a classroom setting, which according to structural functionalism hold that education expanded to meet the demands of an increasingly complex industrialized society s demand for skilled workers, moral and cultural consensus, and for equality of opportunity (Gelles & Levine 1995). Studies have identified that quality of human capital has a significant relationship with nation s economic growth (Musa & Dauda, 2014). Indicating that, schooling, labour force quality and cognitive skills of the population have close relation to economic development. The common measurement of quality human capital is the level of school attainment in a country. As stressed by Ekundayo, (2010), education cannot be an instrument par excellence for achieving national development where secondary education is not effectively managed to accomplish its aims and objectives. This is why learning needs of secondary school have personal and social dimensions, required to enable them survive, develop their full capacities and improve the quality of their lives. The curriculum features a wide range of subjects at secondary levels, which ensures a broad-based education for students and has implications for opportunity for education of a higher level; cater for the differences in talents, opportunities and future roles (Ifenkwe, 2013). Nigeria has witnessed a remarkable decline in academic performance among the secondary school candidate judged by secondary school leaving examination conducted by West African Examination Council (WEAC) including the National Examinations Council (NECO). As observed by Sam (2011), that academic excellence had since departed from the land evidenced by past records of decline in performance of students in the two standard examinations (WAEC and NECO). Dike (2014) highlighted the past three academic year results released by WAEC; In 2010 May/June only 337,071 out of 1,351,843 candidates obtained five credits, including English Language and Mathematics. In Nov/Dec 2012 and 2013, 150,615 (37.97 per cent) out of 413,266 candidates and 86,612 (29.17per Proceedings of ICERI2015 Conference 16th-18th November 2015, Seville, Spain 1959 ISBN:

2 cent) out of 308,217 that wrote the exam passed the examination with five credits, including English Language and Mathematics respectively. The result for 2014 May/June attracted an alarming concern from stakeholders at all level, because it is adjudged the poorest results recorded in last preceding three years (Dike, 2014). Considering this decline with no specific solution in view, it is imperative to investigate the likely causes and find appropriate solution to this national challenge in order enhance sustainable human capital growth and economic development. While there is no argument that the challenges facing students in 21 st century are enormous especially the adolescents in secondary schools in distress and adverse neighbourhood environment, It is worrisome that only few studies have devoted attention to the interrelationships between neighbourhood environment (such as poverty, violence and its associate stress and crime) and reading culture, academic learning and performance, school dropouts, unemployable school leavers and the existence of widening gap in economic opportunities. The paper examined association between urban neighbourhood disadvantages with poor cognitive and behavioural disposition on schooling, learning and performance. Neighborhood is conjectured in this study as conglomerations of various elements of environmental condition in a geographically or socially defined environment that are distinct from other adjoining communities or cities. Although, there are several thinkable factors, the selected variables in this study are those perceived by respondents and those that can be assessed quantitatively. This measured also followed the pattern of City Environmental Quality Review (CEQR) While the neighbourhood can affect community project negatively, its impacts on the potential of the community as well as the children as the element of the community especially the school age can also be verified. This study is therefore premised on the neighbourhood assessment principle which indicates the necessity for neighbourhood assessment if a subject, event or project is going to be affect by neighbourhood indices such as cultural resources (belief, attitude), transportation, noise, land use, public policy, and socio-economic conditions (CEQR Technical Manual, 2014). Previous research on schooling and learning outcome has provided consistent findings that individual factors in making the right decisions are important determinants. In Yaman (2014), attitude causes a person to show certain behaviour and reactions against certain people, objects, and conditions and when positive and negative situations change, cognitive and behavioural perception for that object is re-arranged. Thus according to him, affective behaviour consists of students attitudes, values, motivations, incentives, and so on. However, there is evidence that neighbourhood itself exerts an influence in molding children s lives with physical and social characteristic that can affect children s development. The mechanism connecting individual and family behaviour and outcomes to their residential contexts have been linked to various school-level, peer-group-level, individual-level, and neighbourhood-level processes (Sykes & Kuyper, 2009). The type and condition of housing, yards, streets, sidewalks, recreational facilities, and businesses in a neighbourhood have an impact on children s activities and developmental opportunities. Even more important, children are influenced by other people who live in the neighbourhood and their activities, values, belief, and resources. Having affluent neighbours is associated with positive developmental outcomes in both early childhood and adolescence. Research results have suggested that neighbourhoods have their effects on children and adolescents by means of collective socialization, in which adults in a neighbourhood provide role model and mentoring for local children, rather than by means of behavioural contagion, in which negative peer influences spread problem behaviour (DeHart, Sroufe & Cooper, 2004). Evidence from neighbourhood effects is thought to be particularly strong when educational outcomes are considered, with studies documenting area-based influences on outcomes such as educational attainment (Sykes & Kuyper, 2009; CEQR Technical Manual, 2014). As already pointed out in Harding (2009), adolescence is a developmental stage associated both with greater experimentation and risktaking and with greater focus on social identities and peers, making teenagers particularly susceptible to the influence of cultural heterogeneity in their decision making. It is also a life stage in which important educational decisions are made, chief among them whether to finish high school and whether to enroll in college. As they make these decisions, the adolescents who live in disadvantaged neighborhoods face individual, family, and school-based structural barriers to educational attainment. 1960

3 Although stakeholders in education and considerable previous literatures has documented high level of distrust in teachers competency, lack of good facilities, dropping reading culture and lack of motivation of teachers by governments (Ogundele, Olanipekun & Aina, 2014; Ifenkwe, 2013; Ekundayo, 2010), relatively little is known about correlates of students poor performance which could also be adduced to several socio-psychological factors or intervening variables (Yoloye, 2004; Adeyemo, 2005). The goal of this study is to examine the association of urban neighbourhood disadvantages with poor cognitive and behavioural disposition to schooling and learning. 2 METHODS Data for the study were extracted from a cross sectional survey among senior secondary schools students in Lagos metropolis. The sampling size determination technique used indicated a total of 1400 respondents, however only 1220 could be achieved. Similarly, equal proportions of 100 students each across 14 secondary schools (private and public) in the selected metropolis were planned. The attrition rate (12.9%) was due to school schedules that only permitted the interviews during students break/free periods. Respondents were selected randomly across three of the senior classes (SSS1-3). The state was selected for being a representative of tribe and culture, urban rich and poor setting. The study adopted a measuring scale for both adverse environment and students disposition. The young boys and girls completed about 40 minutes interview and administered questionnaire with questions on attitude towards education, attendance demographic information about the family, peer and neighbourhood characteristics. The study adopted a multi-stage sampling technique, to select a representative sample from the study population drawn from the secondary schools. The first stage of the sampling process involved stratification of Lagos State into advantaged and disadvantaged neighbourhoods. Seven secondary schools were selected randomly from each neighbourhood. 2.1 Measures At the individual level, the dependent variable is self-rated attitude to schooling. Respondents were asked to evaluate their academic performance as poor, fair, good, or excellent. This procedure followed Dahlberg, Toal, Swahn & Behrens (2005) 4-likert scale measurement of attitude and belief on schooling. The obtained responses were later categorized into two (poor/fair and good/excellent) coded as 0 and 1 respectively. The reliability and validity of this scale have been tested and reported elsewhere. Demographic characteristic were predictors and were self-reported responses from the participants. Age was treated as a continuous variable while gender treated as a dichotomous variable (males = 1 and females = 0). Socioeconomic was captured in relations to parents and guidance employment statuses including educational attainment. In the measurement of neighbourhood Level, we utilized variables that capture community social environment. The students were interviewed about the perception of their neighbourhood and social ties with their neighbours. This is captured statistically using Compendium of Assessment Tools scale adapted from Dahlberg, Toal, Swahn and Behrens (2005). The indices measured included social capital, social cohesion, social control and social disorder and violence. These indicators were treated in using a likert scale type. The questionnaire was designed in a way that both attitude and neighbourhood factors responses were captured. The instrument was divided into three Sections (A, B and C). Section A covered the socio-demographic characteristics of the respondents. Section B contained index of attitude, while Section C featured neighbourhood factors. The responses generated from these sections helped to establish the foundation upon which the study could be situated in its context. Although, in-depth interviews were also conducted among the school and government officials, details of this report was not presented here. The in-depth interviews were used primarily to explore official thoughts, feelings, and policies (where available) on schooling. 1961

4 2.2 Analysis and Model Data gathered were analyzed using both descriptive and inferential statistical methods. Returned questionnaire returned were edited, coded and entered in the computer accordingly. The data were analyzed using the Statistical Package for Social Sciences (SPSS 22). While the descriptive analysis featured only frequency distributions in tabular arrangements of relevant variables were presented, the multivariate segment used the binary logistic regression technique to estimate the hypothesis formulated to evaluate the influence of neighbourhood conditions and attitude toward schooling on academic performance. The general format for the two models is represented as: Where, α (alpha) is the Y-intercept, i.e. the estimated value of Y when all Xs are set at zero (0). Each (Beta) represents a regression coefficient measuring the expected change in Y per unit change in any X assuming that all other Xs are held constant. Y which equals therefore measures the logodds of good/excellent performance given certain neigbhourhood circumstances. The X s are selected respondents characteristics and neigbhourhood traits considered as likely predictors of excellent academic performance among the subjects. In the model, the dependent variable is academic performance, while the predictors (independents variables) are set of indicators of neighbourhood conditions such as: social control in the community, parents understanding of their child/ward, exposure to social vices (e.g. drugs), and prevalence of security disorder (shooting in the environment). The second model (Model II) evaluated the influence of respondents attitudinal factors on their academic performance. While the dependent variables remain academic performance, the independent variables consist of indicators of attitudinal disposition. 3 RESULTS 3.1 Demographic Characteristics of Respondents Table 1 displays the background information about the respondents. The respondents were distributed in the ratio of 58:42 between public and private schools. The gender distribution follows the national distribution with more male than female. The school attendance rate of 53.8 and 46.2% followed also national pattern where the male secondary school enrolment rate is slightly higher than that of female as indicated in Table 1. The mean age observed is 13.7 year. The self reported measurement of academic performance revealed that more than half of the students considered themselves above average in academic performance as judged by school or past examination results. Relatively 42.5% indicated they are excellent (13.2%) and good (29.3%) by the result standard while 44.2% and 13.3% rated themselves very low in terms of academic standard in their various schools. The education status of the parents indicated that they are all literates and have had primary school education and above (Table 1). However, the report shows that majority of the students (66.1%) have parents that have attained above secondary education. Only two major occupation categories were used namely (1) Self-employed and (2) Employee. This is justified since the study is not focused on parental demographics but the environment/neighbourhood circumstances that influence the child s academic performance. More than half of the parents of respondents work as employees. Further investigation revealed they work in ministries and as employees of other private establishments. 1962

5 Table 1. Selected Background Information about the Respondents Selected Variables Frequency % School Category Public Private Total Sex Male Female Total Age Group Less than 14 years years Total Academic Performance Excellent Good Fair Poor Total Parent Educational Attainment Primary Secondary school Tertiary Total Parents Occupation Self Employed Employee Total Source: Field Survey Neighbourhood, Attitude towards Schooling and Academic Performance The result of the multivariate analysis is presented in Table 2. The model estimated the interrelationships between selected indicators of neighbourhood, attitudinal factors and academic performance were computed in Model 1 to identify attitudinal correlates of academic performance. In the model, the dependent variable was measured as respondent academic performance. This was classified into five according to whether it is excellent, good, fair, or poor as at the time of the survey. These were re-classified into two. The first two categories were re-coded as good performance, coded as 1 while the last two were grouped as poor result and coded as 0 in order to satisfy the condition for binary logistic regression model. The model thus measures the academic performance through respondent s change from poor performance ( 0 ) to good performance ( 1 ). It specifically considered the probability of achieving good academic performance given certain traits of neighbourhood and attitude towards schooling and learning. In order to achieve robust result, certain cofounding variables (intervening variables) were adjusted for in the binary logistic analysis. These include age, parental education and parents working condition. 1963

6 Those in this age level age are less likely to have good academic performance. The variable is statistically significance at p-value = (Table 2). Respondents disposition to the school they are attending demonstrates significance relationship with academic performance. Those who dislike their school including those that prefer it fairly are less likely to earn good academic performance (Beta = , and ) respectively. The p-values of and demonstrate statistical significance levels as indicated in Table 2. Table 2. Binary Regression illustrating the influence Neighbourhood conditions and attitude towards schooling on Academic Performance Selected Variables B S.E. Wald Sig. Exp(B) Age Group Less than Attitude to the School - Extremely like the school RC Like the school fairly Dislike the school greatly Dislike the school fairly Bad Road/Traffic Somewhat good RC Fair Extremely bad Parent/Guardian Status Rich/Comfortable RC Poor/Not Comfortable School Activities Boring Strongly agree RC Agree Disagree Strongly Disagree Noisy Environment/Pollutant Agree Strongly Agree Disagree Strongly Disagree Constant Log likelihood = ; Cox & Snell R Square = Nagelkerke R Square = Overall Percentage = 68.9 Source: Field Survey 2015 RC =Reference Category Among the neigbhourhood factors tested is bad road and traffic congestion as being experienced by the respondents. The analysis output indicated that whether the road is fair or bad, it is disincentive to schooling. The variable measures as somewhat good, fair and extremely bad exhibited negative association with good academic performance. They are statistically significance at p-value and 0025 respectively (see Table 2). Poor parents background is negatively associated B = ) with good academic result. The result revealed that students with parent in low economic status are less likely to earn good academic result. The perception about school activities have negative effects on academic performance however, they are not statistically supported (the p-values are higher than 5 %). Whenever the candidates experience noisy environment or other social vices, the respondents 1964

7 are less likely to have good academic performance. Notwithstanding, those who refuted the existence of noisy and polluted environment (by answering disagree and strongly disagree) are and times more likely to experience good academic performance (Table 2). The overall appraisal of the model indicated that the model accurately predicted the outcome results up to 69.9%. However, the variation in the academic performance that are explained by the predictors are 63% (Nagelkerke R Square = 0.630) and 45% (Cox & Snell R Square = 0.451), respectively. 4 DISCUSSION This study is posited as extension of previous studies on academic performance in secondary school because it included the interconnections between neigbhourhood conditions and academic outcomes. It provided evidences that at secondary school, age of the student, personal perception about the school, socio-economic status of the parents as well as characteristics of immediate physical and broader social environment are veritable correlates of academic performance. While previous literature such as Ogundele et al (2014); Ifenkwe (2013); and Ekundayo (2010) have highlighted the provision of infrastructure, review of curriculum, lack of qualify teachers and so on, as important factors in academic performance, data from this study revealed that individual factors and society support are important determinants of academic success in secondary school. Notably, our analysis shows that academic performance may be associated with individuals action and belief in academic processes. Individual must be able to see him/herself as really belong at school and determine to do in school, try hard to perform better, do extra work to improve grades, and believe in important of learning to later life achievement. Creating affective behaviour towards learning will go a long way to improve academic performance in past research findings (CEQR Technical Manual, 2014; Yaman, 2014). Also, lack of parental control, stressful urban bad road and heavy traffic, exposure to anti social/illegal activities (e.g. drugs) including elements of neighborhood disorganization (e.g. riot) are inhibiting factors and disincentives to academic success. We observed that poor neighbourhood may engender absence of some level of encouragement needed to pursue academic achievement. This is not strange, as Thomas, Torrone, and Browing (2010) found, for example, neighbourhood characteristic such as social capital, social disorder can be associated with rates of infections in neighbourhoods. Also neighbourhood poverty, disorder, deterioration of the built environment, and have been associated with biological indicators of stress and depression. Therefore, exposure in disadvantaged neighbourhood can be a major distraction and setback in academic achievement. 5 CONCLUSION AND RECOMMENDATIONS The study presented the meaning of neigbhourhood in Nigerian context and specifically highlighted the importance of neighbourhood conditions, attitude towards schooling and learning as significance factors in estimating academic performance. It is however at variance with previous literature that emphasised the provision of infrastructure, review of curriculum, lack of qualified teachers and so on as correlates of good academic performance. The study posits that individual factors and society supports are sin-qua-non in the evaluation of academic performance. The analysis also demonstrated that parents socio-economic status, noisy environment, bad road and traffic congestion. This research is important to understanding how neighbourhood disadvantaged features are related to attitude and academic performance. The indices can be use to evaluate new area for educational policy and performance interventions foe secondary school students in Nigeria. Succinctly put, that adverse neighbourhood characteristics in urban center are connected with the poor learning attitude and learning outcomes. The authors recommended simultaneous emphasis on attitudinal change motivations and compulsory secondary education policy initiatives in Nigeria and across other sub- Saharan African countries. REFERENCES [1] Adeyemo, D.A (2005) Parental Involvement, Interest in Schooling and School Environment as a Predictor of Academic Self-efficiency among Fresh Secondary School Students in Oyo State, Nigeria, Electronic Journal of Psychology of Education, 5(3): 1-15 [2] Dahlberg LL, Toal SB, Swahn M, Behrens CB. (2005) Measuring Violence-Related Attitudes, Behaviors, and Influences among Youths: A Compendium of Assessment Tools, 2nd ed., 1965

8 Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. [3] DeHart, G. B. Sroufe, L. A. and Cooper, R. G. (2004) Child Development: Its Nature and Curse (5 th Edition).New York McGrawHill. [4] Dike, G (2014) Outrage Trails Students Poor Performance in 2014 WASSCE: The Sun Newspaper; Retrieved, September [5] Ekundayo, H.T (2010) European Journal of Educational studies 2(3), pg [6] Gelles, R.J and Levine, A (1995) Sociology: An Introduction (5 th Edition) USA; McGraw-Hill Inc. [7] Harding, D. J (2009) Neighbourhood Cultural Heterogeneity, College Goals, and College Enrollment. Population Study Center: University of Michigan Institute for Social Research. [8] Ifenwe, G.E (2013) Educational Development in Nigeria; Challenges and Prospects in the 21 st century. Universal Journal of Education and General Studies, 2(1) pp [9] Memory Q., Memory B. (2013). Corrupt Academic Practices in Nigerian Educational System. Journal of Education and Practice, 4(27) pg [10] Musa, M and Dauda, E.S (2014) Trends Analyses of students Mathematics Performance in West African Senior Secondary Certificate Examinations from 2004 to 2013; Implication for Nigeria s Vision 20:2020; British Journal of Education, 2(7) pg [11] Ogundele, G.A; Olanipekun, S.S and Aina, J.K (2014) Causes of Poor Performance in West African School Certificate Examination (WASSCE) in Nigeria. Journal of Arts, Humanities and Social Sciences. 2(5b); [12] Sam. O. (2011) Mass Failure Worries Stakeholders. Sun Newspaper, [13] Sykes, B. and Kuyper, H. (2009) Neighbourhood Effects on Youth Educational Achievement in the Netherlands: Can Effects be Identified and Do they vary by Student Background Characteristics? Environmental and Planning, 41, [14] Thomas, C. Torrone, E. A. and Browing, C. R (2010) Neighbourhood Factors Affecting Rates of Sexually Transmitted Disease in Chicago. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 87(1), [15] Yaman, H. (2014). The Relation General Anxiety Level, Anxiety of Writing, and Attitude for Turkish Course of Secondary School Students. Educational Sciences: Theory & Practice, 14(3), [16] Yoloye, T.W.B (2004). That we may Learn Better. An inaugural lecture presented on 7 th October, University of Ibadan [17] City Environmental Quality Review (CEQR) (2014). Neighborhood Character, Chapter 21. CEQR Technical Manual, March 2014 Edition. City Environmental Quality Review Technical Manual Mayor s Office of Environmental Coordination, New York City